---
language:
- as
- bn
- brx
- doi
- en
- gom
- gu
- hi
- kn
- ks
- kas
- mai
- ml
- mr
- mni
- mnb
- ne
- or
- pa
- sa
- sat
- sd
- snd
- ta
- te
- ur
language_details: >-
  asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr,
  hin_Deva, kan_Knda, kas_Arab, kas_Deva, mai_Deva, mal_Mlym, mar_Deva,
  mni_Beng, mni_Mtei, npi_Deva, ory_Orya, pan_Guru, san_Deva, sat_Olck,
  snd_Arab, snd_Deva, tam_Taml, tel_Telu, urd_Arab
tags:
- indictrans
- translation
- ai4bharat
- multilingual
license: mit
datasets:
- flores-200
metrics:
- bleu
- chrf
- chrf++
- comet
inference: false
---

# IndicTrans2

This is the model card of IndicTrans2 Indic-En 1.1B variant.

Here are the [metrics](https://drive.google.com/drive/folders/1lOOdaU0VdRSBgJEsNav5zC7wwLBis9NI?usp=sharing) for the particular checkpoint.

Please refer to `Appendix D: Model Card` of the [preprint](https://arxiv.org/abs/2305.16307) for further details on model training, intended use, data, metrics, limitations and recommendations.


### Usage Instructions

Please refer to the [github repository](https://github.com/AI4Bharat/IndicTrans2/tree/main/huggingface_inference) for a detail description on how to use HF compatible IndicTrans2 models for inference.


### Citation

If you consider using our work then please cite using:

```
@article{ai4bharat2023indictrans2,
  title   = {IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
  author  = {AI4Bharat and Jay Gala and Pranjal A. Chitale and Raghavan AK and Sumanth Doddapaneni and Varun Gumma and Aswanth Kumar and Janki Nawale and Anupama Sujatha and Ratish Puduppully and Vivek Raghavan and Pratyush Kumar and Mitesh M. Khapra and Raj Dabre and Anoop Kunchukuttan},
  year    = {2023},
  journal = {arXiv preprint arXiv: 2305.16307}
}
```